Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice

Bayesian spatial-temporal analysis and determinants of cardiovascular diseases in Tanzania mainland

BACKGROUND

Cardiovascular Diseases (CVDs) are health-threatening conditions that account for high mortality in the world. Approximately 23.6 million deaths due to CVD is expected in the year 2030 worldwide. The CVD burden is more severe in developing countries, including Tanzania.

OBJECTIVES

This study analyzed the spatial-temporal trends and determinants of cardiovascular diseases in Tanzania from 2010 to 2019.

METHODS

Individual data were extracted from Jakaya Kikwete Cardiac Institute (JKCI), Mbeya Zonal Referral Hospital (MZRH), Kilimanjaro Christian Medical Centre (KCMC) and Bugando hospitals and the geographical data from TMA. The model containing spatial and temporal components was analyzed using the Bayesian hierarchical method implemented using Integrated Nested Laplace Approximation (INLA).

RESULTS

The results found that the incidence of CVD increased from 2010 to 2014 and decreased from 2015 to 2019. The southern highlands, lake, central and coastal zones were more likely to have CVD problems than others. It was also revealed that people aged 60-64 years OR = 1.49, females OR = 1.51, smokers OR = 1.76, alcohol drinkers OR = 1.48, and overweight OR = 1.89 were more likely to have CVD problems. Additionally, a 1oC increase in the average annual air maximum temperature was related to a 14% risk of developing CVD problems. The study revealed that the model, which included spatial and temporal random effects, was the best-predicting model.

CONCLUSION

The study shows a decreased CVD incidence rate from 2015 to 2019. The CVD incidences occurred more in Tanzania's coastal and lake areas between 2010 and 2019. The demographic, lifestyle and geographical risk factors were significantly associated with the CVD.

The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation

Cardiovascular Disease (CVD) is currently the major challenge to people's health and the world's top cause of death. In Tanzania, deaths due to CVD account for about 13% of the total deaths caused by the non-communicable diseases. This study examined the spatio-temporal clustering of CVDs from 2010 to 2019 in Tanzania for retrospective spatio-temporal analysis using the Bernoulli probability model on data sampled from four selected hospitals. Spatial scan statistics was performed to identify CVD clusters and the effect of covariates on the CVD incidences was examined using multiple logistic regression. It was found that there was a comparatively high risk of CVD during 2011-2015 followed by a decline during 2015-2019. The spatio-temporal analysis detected two high-risk disease clusters in the coastal and lake zones from 2012 to 2016 (p<0.001), with similar results produced by purely spatial analysis. The multiple logistic model showed that sex, age, blood pressure, body mass index (BMI), alcohol intake and smoking were significant predictors of CVD incidence.

A timeliness analysis of emergency services and cardiovascular outcomes in cardiac patients referred through prehospital emergency services between 2020 and 2023: a cross-sectional study in Iran

OBJECTIVE

Effective time management is crucial for the survival of all patients, particularly those with cardiovascular conditions. This is especially true in the context of pre-hospital emergency services, where prompt intervention can significantly impact outcomes. This study delves into the timeliness of emergency services and the subsequent outcomes for hospitalized cardiovascular patients in EMS center in Fasa University of Medical Sciences, southern Iran.

RESULTS

A total of 4972 emergency calls related to cardiac diagnoses were received between 2020 and 2023. The transport time was significantly correlated with age, location of the mission, and type of mission. Of the total, 86 underwent angioplasty within the standard time of less than 90 min, of which 81 were discharged and 5 died. 51 patients underwent angioplasty after more than 90 min, of which 47 were discharged and 4 died. In addition, 124 of these patients experienced cardiopulmonary resuscitation, of which 63 were successful and 61 were unsuccessful.

A retrospective study of Crimean-Congo hemorrhagic fever in Iraq

Background

CCHF is transmitted via ticks biting and directly by contact with tissue or blood of infected patients or viremic animals. This study intends to determine the occurrence of CCHF in Iraq between 2015 and 2019.

Methods

This study was designed as a retrospective and descriptive cross-sectional study. It was approved the occurrence of CCHF in Iraq with relation to some epidemiological and demographic data reported in the Iraqi Communicable Diseases Control Center (CDC)/zoonotic diseases section between 2015-2019.

Results

Out of 206 suspected cases, only 17 were diagnosed as CCHF with a total fatality ratio of 52%, 25%, and 80% in 2015 and 2018 respectively. However, no mortality was reported during 2016, 2017, and 2019. The mean age of the patients was 33 years± 18 SD, in males mainly (76%). Moreover, the risk groups were 29 %, 23 %, 18 % 12 %, and 6 % for butchers, animal dealers, gainers, both housewives and students and children respectively.

Conclusion

Strict precautions and precise surveillance should be implemented to control the disease and protect the community by improving the diagnosis and treatment of CCHF. The authors recommend another future study to detect the genotyping and sequencing of CCHFV in Iraq.

Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

This study integrates geographical information systems (GIS) with a mathematical optimization technique to enhance emergency medical services (EMS) coverage in a county in the northeast of Iran. EMS demand locations were determined through one-year EMS call data analysis. We formulated a maximal covering location problem (MCLP) as a mixed-integer linear programming model with a capacity threshold for vehicles using the CPLEX optimizer, an optimization software package from IBM. To ensure applicability to the EMS setting, we incorporated a constraint that maintains an acceptable level of service for all EMS calls. Specifically, we implemented two scenarios: a relocation model for existing ambulances and an allocation model for new ambulances, both using a list of candidate locations. The relocation model increased the proportion of calls within the 5-minute coverage standard from 69% to 75%. With the allocation model, we found that the coverage proportion could rise to 84% of total calls by adding ten vehicles and eight new stations. The incorporation of GIS techniques into optimization modelling holds promise for the efficient management of scarce healthcare resources, particularly in situations where time is of the essence.

A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran

BACKGROUND

Despite significant advances in the quality and delivery of specialized stroke care, there still persist remarkable spatial variations in emergency medical services (EMS) transport delays, stroke incidence, and its outcomes. Therefore, it is very important to investigate the possible geographical variations of in-hospital stroke mortality and to identify its associated factors.

METHODS

This historical cohort study included suspected stroke cases transferred to Ghaem Hospital of Mashhad by the EMS from March 2018 to March 2019. Using emergency mission IDs, the pre-hospital emergency data were integrated with the patient medical records in the hospital. We used the Bayesian approach for estimating the model parameters.

RESULTS

Out of 301 patients (142 (47.2%) females vs. 159 (52.8%) males) with a final diagnosis of stroke, 61 (20.3%) cases had in-hospital mortality. Results from Bayesian spatial log-logistic proportional odds (PO) model showed that age (PO=1.07), access rate to EMS (PO=0.78), arrival time (evening shift vs. day shift, PO=0.09), and sequelae variables (PO=9.20) had a significant association with the odds of in-hospital stroke mortality (P<0.05). Furthermore, the odds of in-hospital stroke mortality were higher in central urban areas compared to suburban areas.

CONCLUSION

Marked regional variations were found in the odds of in-hospital stroke mortality in Mashhad. There was a direct association between age and odds of in-hospital stroke mortality. Hence, the prognosis of in-hospital stroke mortality could be improved by better control of hypertension, prevention of the occurrence of sequelae, increasing the access rate to EMS, and optimizing shift work schedule.

Developing and validating cardiovascular emergency gamification question cards

BACKGROUND

Learning to handle cardiovascular emergencies is complex and can cause psychological stress for nursing students. Gamification using question cards as a learning aid is one of the creative educational strategies that can help students learn in a fun way. The design of cards with valid and reliable questions is essential in gamification; however, such cards are still lacking in cardiovascular emergency learning.

OBJECTIVES

To develop and validate cardiovascular emergency question cards for the future use of gamification for education regarding cardiovascular emergencies among undergraduate nursing students.

METHODS

The development process included two phases: designing the question cards and testing validity evidence. A table of specifications was used to select and assign questions based on three levels with six learning outcome categories. Five nurse experts assessed the evidence based on test content, including the relevance, clarity, and essentiality of the questions. Seven final-year nursing students evaluated the evidence based on the response process. After revision, 61 nursing students evaluated the internal consistency reliability of each level.

RESULTS

In the design phase, ninety English question cards were categorized into three levels based on the learning outcomes expected in an undergraduate emergency nursing course. Most of the questions were multiple-choice questions, and some were short answer questions. The final item-content validity index = 1.00, the scale-content validity index/universal agreement = 1.00, and the content validity ratio = 1.00. Cronbach's α for internal structure was 0.81 for level I (n = 61), 0.92 for level II (n = 54), and 0.81 for level III (n = 46).

CONCLUSION

The cardiovascular emergency question cards showed acceptable evidence based on the test content, response process, and internal structure. In the future, testing the feasibility of applying the question cards to gamification and assessing their learning effect on cardiovascular emergency knowledge retention will be necessary.

One-year spatiotemporal database of Emergency Medical Service (EMS) calls in Mashhad, Iran: data on 224,355 EMS calls

Objectives

Emergency Medical Services (EMS) is the first point of service for the people who are in critical condition and in need of urgent health care. In Iran, as in other countries, people in need of emergency services often die or are left with a permanent injury due to the poor EMS-related infrastructure. It has been shown that a detailed examination of the response times and the spatiotemporal pattern of EMS calls for service can lead to improvements in time-sensitive patient outcomes. We performed a spatiotemporal study in city of Mashhad, the second-most populous city of Iran, to investigate the pattern of the EMS calls and now wish to release a comprehensive dataset resulting from this study.

Data description

The data include three data files plus a data dictionary file. Data file 1 contains the characteristics of EMS requests including sex, age group, date of call, different time periods of each EMS missions, the census tracts’ ID of callers, the chief complaint, and the EMS mission result. Two spatial data files include the boundaries of the census tracts in Mashhad and the point location of all EMS stations, respectively. A data dictionary file defines all fields and values across the data files.

Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach

Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disaster. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, particularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clusters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.

Development of a web-geographical information system application for plotting tuberculosis cases

In the last few decades, public health surveillance has increasingly applied statistical methods to analyze the spatial disease distributions. Nevertheless, contact tracing and follow up control measures for tuberculosis (TB) patients remain challenging because public health officers often lack the programming skills needed to utilize the software appropriately. This study aimed to develop a more user-friendly application by applying the CodeIgniter framework for server development, ArcGIS JavaScript for data display and a web application based on JavaScript and Hypertext Preprocessor to build the server's interface, while a webGIS technology was used for mapping. The performance of this approach was tested based on 3325 TB cases and their sociodemographic data, such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency status, and smoking status between 1st January 2013 and 31st December 2017 in Gombak, Selangor, Malaysia. These data were collected from the Gombak District Health Office and Rawang Health Clinic. Latitude and longitude of the location for each case was geocoded by uploading spatial data using Google Earth and the main output was an interactive map displaying location of each case. Filters are available for the selection of the various sociodemographic factors of interest. The application developed should assist public health experts to utilize spatial data for the surveillance purposes comprehensively as well as for the drafting of regulations aimed at to reducing mortality and morbidity and thus minimizing the public health impact of the disease.

Spatial accessibility to health care services among children with cerebral palsy in Johor, Peninsular Malaysia

Cerebral palsy (CP) is one of the most common causes of disability in childhood, leading to functional limitations and poor nutritional status. Families with CP children face challenges in providing proper care. Thus, accessibility of CP patients to health facilities is important to ensure that they can maintain regular visits to health facilities for proper treatment and care. The current study aimed to map the spatial distribution of CP in Johor, Malaysia and measure the accessibility of CP patients to nearby hospitals, health clinics and community-based rehabilitation centres. The study is based on CP cases in 2017 obtained from the Department of Social Welfare, Malaysia and analysed using the average nearest neighbour, buffer analysis and Kernel Density Estimation. Results indicate that there is generally good access to health care services for many of the CP children in Johor, but for 25% of those living more than 10 km away from the health clinics or community-based rehabilitation centres, regular visits can be a problem. This information should be used for targeted intervention and planning for health care strategies. Furthermore, information on hospital accessibility of CP children would allow for planning of proper and regular treatment for these patients. The study has shown that it is possible to improve the understanding of the distribution of CP cases by integrating spatial analysis using geographical information systems without relying on official information about the density of populations.

Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model

BACKGROUND

There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran.

METHODS

The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model.

RESULTS

There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services.

CONCLUSIONS

The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.

Religious Affiliation, Daily Spirituals, and Private Religious Factors Promote Marital Commitment Among Married Couples: Does Religiosity Help People Amid the COVID-19 Crisis?

Religious studies are a vital branch of social science that seeks to explain the beliefs of human society and deals with the practices and beliefs of individuals. This distinctive study focuses on such influential aspects of a healthy life, which could play a vital role in the marital quality and matrimonial commitment of individuals. The study principally focused on inspecting the role of religiosity in healthy marital commitment among individuals. It is a distinctive and central value in regulating a healthy social life. This research designed a conceptual model for assessing marital commitment, and the study model comprised two primary variables. The study received datasets through a survey questionnaire based on participants from five private and public sectors. The research study conducted an empirical analysis to test the proposed conceptual framework. The findings exhibited that the value of the R 2 model was 0.484, meaning the level of religiosity had a substantial impression on healthy and lasting marital commitment. According to the final outline of the model factors associated with building religious support factors (β = 0.491), the marital commitment had a better and healthier impact. The goodness-of-fit of the measurement of the conceptual model showed a value of 0.51, which indicated that the theoretical model had sufficient consistency and rationality, and accurately fitted the data. Such an advanced statistical model is missing from the previous literature. The study results provide helpful insight to elucidate the social dynamics of marital commitment. The findings designate that religious practices strengthen and promote nuptial commitment. The study is novel in the context of religiosity impact on martial commitment with a cultural background of Pakistan. The generalizability of the study does not apply to the entire population or other regions. Future studies can investigate other religious variables to explore further research findings. The findings are helpful for decision-makers and policymakers to concentrate on marital issues and challenges confronted by couples worldwide.

A spatial-epidemiological dataset of subjects infected by SARS-CoV-2 during the first wave of the pandemic in Mashhad, second-most populous city in Iran

OBJECTIVE

In March 2020, Iran tackled the first national wave of COVID-19 that was particularly felt in Mashhad, Iran's second-most populous city. Accordingly, we performed a spatio-temporal study in this city to investigate the epidemiological aspects of the disease in an urban area and now wish to release a comprehensive dataset resulting from this study.

DATA DESCRIPTION

These data include two data files and a help file. Data file 1: "COVID-19_Patients_Data" contains the patient sex and age + time from symptoms onset to hospital admission; hospitalization time; co-morbidities; manifest symptoms; exposure up to 14 days before admission; disease severity; diagnosis (with or without RT-PCR assay); and outcome (recovery vs. death). The data covers 4000 COVID-19 patients diagnosed between 14 Feb 2020 and 11 May 2020 in Khorasan-Razavi Province. Data file 2: "COVID-19_Spatiotemporal_Data" is a digital map of census tract divisions of Mashhad, the capital of the province, and their population by gender along with the number of COVID-19 cases and deaths including the calculated rates per 100,000 persons. This dataset can be a valuable resource for epidemiologists and health policymakers to identify potential risk factors, control and prevent pandemics, and optimally allocate health resources.

The Role of Social Media in the Advent of COVID-19 Pandemic: Crisis Management, Mental Health Challenges and Implications

BACKGROUND

This study focuses on how educating people through social media platforms can help reduce the mental health consequences of the COVID-19 to manage the global health crisis. The pandemic has posed a global mental health crisis, and correct information is indispensable to dispel uncertainty, fear, and mental stress to unify global communities in collective combat against COVID-19 disease worldwide. Mounting studies specified that manifestly endless coronavirus-related newsfeeds and death numbers considerably increased the risk of global mental health issues. Social media provided positive and negative data, and the COVID-19 has resulted in a worldwide infodemic. It has eroded public trust and impeded virus restraint, which outlived the coronavirus pandemic itself.

METHODS

The study incorporated the narrative review analysis based on the existing literature related to mental health problems using the non-pharmaceutical interventions (NPIs) approach to minimize the COVID-19 adverse consequences on global mental health. The study performed a search of the electronic databases available at PsycINFO, PubMed, and LISTA. This research incorporates the statistical data related to the COVID-19 provided by the WHO, John Hopkins University, and Pakistani Ministry of Health.

RESULTS

Pakistan reported the second-highest COVID-19 cases within South Asia, the fifth-highest number of cases in Asia after Iran, India, Russia, Saudi Arabia, and the 14th highest recorded cases, as of October 14, 2020. Pakistan effectively managed the COVID-19 pandemic in the second wave. It stands at the eighth-highest number of confirmed cases in Asia, the 3rd-highest in South Asia, and the 28th-highest number of established patients globally, as of February20, 2021.

CONCLUSION

The COVID-19 has resulted in over 108.16 million confirmed cases, deaths over 2.374 million, and a recovery of 80.16 million people worldwide, as of February 12, 2021. This study focused on exploring the COVID-19 pandemic's adverse effects on global public health and the indispensable role of social media to provide the correct information in the COVID-19 health crisis. The findings' generalizability offers helpful insight for crisis management and contributes to the scientific literature. The results might provide a stepping-stone for conduct future empirical studies by including other factors to conclude exciting developments.